Pore Tensor-Based Constitutive Model of Deep Coral Reef Limestone at High Loading Rates.

The buried diagenesis and dolomitization in the deep stratum of coral reef island enable the Coral reef limestone (CRL) to exhibit a significant distinction compared with the calcified coral skeleton in mechanical properties. This paper utilized the Split Hopkinson Pressure Bar and X-ray computed tomography to investigatethe dynamic mechanical characteristics of deep CRL, revealing the effect of free water on stress–strain behaviors and the energy evolution law of CRL under high-rate impact. Furthermore, the concept of pore tensor proposed in our previous investigation was introduced to modify the dynamic constitutive model. The results indicate that the dynamic compressive strength (DCS) of CRL specimens is strongly related to stress rate, whereas the dynamic elastic modulus and DCS are independent of strain rate. The peak strains of dry specimens are significantly greater than those of saturated ones at comparative loading rates, and the viscosity effect of free water at a high loading rate impedes the deformation of CRL specimens. Moreover, the energy absorption efficiency of CRL is significantly higher than that of Bohus granite and Solnhofen limestone. Dry specimens have higher energy absorption efficiency under the same energy input, but the dynamic increase factor (DIF) of saturated specimens is larger under the same energy absorption efficiency. For the determination of DIF, this paper adopted the Back Propagation Neural Network model trained by pore tensor to predict the quasi-static compressive strength of CRL specimens, which solved the problem of considerable discreteness in mechanical parameters of CRL. The critical transition value of input energy proportion that the DIF increases rapidly is about 30%. In addition, the constitutive model modified by pore tensor reflects the influence of pore structure and water content of CRL specimens, and well describes the characteristics of dynamic elastic modulus and peak strain of deep CRL independent of loading rate. Highlights: Dynamic compressive strength of coral reef limestone strongly correlates with stress rate and weakly correlates with strain rate. The machine learning-based method for predicting quasi-static strength improves the determination accuracy of dynamic increase factor of coral reef limestone. The critical transition value of input energy proportion that the dynamic increase factor increases rapidly is about 30%. The modified constitutive model reflects the effects of pore structure and water content of coral framework limestone. [ABSTRACT FROM AUTHOR]